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Testing in Identification Systems
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-0036-9049
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-7926-5081
2018 (English)In: 2018 IEEE INFORMATION THEORY WORKSHOP (ITW), IEEE , 2018, p. 295-299Conference paper, Published paper (Refereed)
Abstract [en]

We study a hypothesis testing problem to decide whether or not an observation sequence is related to one of users in a database which contains compressed versions of users' data. Our main interest lies on the characterization of the exponent of the probability of the second kind of error when the number of users in the database grows exponentially. We show a lower bound on the error exponent and identify special cases where the bound is tight. Next, we study the c-achievable error exponent and show a sub-region where the lower bound is tight.

Place, publisher, year, edition, pages
IEEE , 2018. p. 295-299
Series
Information Theory Workshop, ISSN 2475-420X
Keywords [en]
Mixture distribution, information-spectrum method, strong converse
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-252670DOI: 10.1109/ITW.2018.8613310ISI: 000467849900060Scopus ID: 2-s2.0-85062066143ISBN: 978-1-5386-3599-5 (print)OAI: oai:DiVA.org:kth-252670DiVA, id: diva2:1321765
Conference
IEEE Information Theory Workshop (ITW), NOV 25-29, 2018, Guangzhou, PEOPLES R CHINA
Note

QC 20190610

Available from: 2019-06-10 Created: 2019-06-10 Last updated: 2019-06-10Bibliographically approved

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Vu, Minh ThànhOechtering, Tobias J.Skoglund, Mikael

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